Update main.py

main.py

@@ -3,37 +3,38 @@ from pydantic import BaseModel
 from typing import List
 import joblib
 import numpy as np
+import os
 
-app = FastAPI(title="Stroke Risk Prediction API")
+app = FastAPI()
 
-# Lazy loading
 model = None
 
-@app.on_event("startup")
 def load_model():
     global model
-    try:
-        model = joblib.load("best_random_forest.pkl")
-    except Exception as e:
-        print(f"Failed to load model: {e}")
-        raise RuntimeError("Model loading failed.")
+    if model is None:
+        model_path = "best_random_forest.pkl"
+        if not os.path.exists(model_path):
+            raise RuntimeError("Model file not found.")
+        model = joblib.load(model_path)
 
 class PredictRequest(BaseModel):
     input_data: List[List[float]]
 
-@app.post("/predict")
-def predict(req: PredictRequest):
-    try:
-        input_array = np.array(req.input_data)
-        predictions = model.predict(input_array)
-        return {"predictions": predictions.tolist()}
-    except Exception as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
 @app.get("/")
-def read_root():
-    return {"status": "ok"}
+def root():
+    return {"message": "API is running."}
 
 @app.get("/health")
 def health():
     return {"status": "healthy"}
+
+@app.post("/predict")
+def predict(data: PredictRequest):
+    try:
+        load_model()  # Only loads once, on first request
+        inputs = np.array(data.input_data)
+        preds = model.predict(inputs)
+        return {"predictions": preds.tolist()}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+